An overview of electronic part failure analysis experience.
Electronic part failure analysis in spacecraft programs, noting quality defects and misuse as major failure cause resulting in malfunction
Wright, L. W.↗
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A study of Mariner 10 flight experiences and some flight piece part failure rate computations
The problems and failures encountered in Mariner flight are discussed and the data available through a quantitative accounting of all electronic piece parts on the spacecraft are summarized. It also shows computed failure rates for electronic piece parts. It is intended that these computed data be used in the continued updating of the failure rate base used for trade-off studies and predictions for future JPL space missions.
Paul, F. A.↗
Development of electronic part failure rates for long-duration space missions.
Abstract missing.
Sicol, R. L.↗
Introduction to EEEE Parts: Failure Mechanisms 101
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John Evans↗
NASA GSFC EEE Parts Failure Analysis: Isolating Integrated Circuit Electrical Damage
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EEE↗
Predicting the strength of filament-wound specimens with surface cuts
The notched strength of filament-wound composite specimens was determined for coupons with various sized semielliptic surface notches. When the part-through notches did not cut the first 0-deg layer the strength was independent of the size of the notch and was equal to the unnotched tensile strength. When the cut penetrated 0-deg layers, the specimens failed in a two-part failure mode. The first part of the failure was modeled using fracture mechanics and a straight line tangent to the fracture mechanics solution, and the second part of the failure was modeled using a failure criterion that accounted for the moduli of 0-deg and helical layers.
Morris, Don H.↗
Handbook of structural stability part IV : failure of plates and composite elements
Available theories on failure of flat plates are reviewed, and test data on the postbuckling behavior, effective width, and failure of flat curved plates are correlated. Test data on the crippling strength of various formed and extruded shapes are reviewed, from which a generalized method of crippling analysis is formulated. This analysis is then applied to a variety of sections and materials in common use.
Gerard, George↗
Reliability Growth Modeling and Testing
Reliability growth has been modelled as an exponential decline in the cumulative failure rate that continues indefinitely as long as testing continues. Contrary to this, most reliability growth data show a brief high initial failure rate due to infant mortality followed by a long period of constant low failure rate. A two part failure rate model with an initial exponential decline followed by a constant failure rate usually fits the data and provides a more realistic description of reliability growth. The reliability growth process consists of testing, experiencing failures, finding the failure causes, and redesigning the system to remove them. The cost of reliability growth increases with the number of inherent failure modes and the time needed for them to occur and be removed. The failure modes with the lower failure rates will tend to occur later, as their Mean Time Before Failure (MTBF) is the inverse of the failure rate. Reliability growth testing has diminishing returns, since it takes longer to find and remove the less probable failures.This paper first discusses the reliability bathtub curve and then explains that reliability growth is produced by testing, identifying failure causes, and designing to remove them. A simple model of reliability growth is introduced, with a brief group of early failures followed by a constant failure rate. The cumulative failure rate n(t)/t can decline as rapidly as1/t or t-1butdeclines more slowly if additiona lfailures occur. The 56-failure Crow data seti s used to demonstrate the two-phase model of reliability growth followed by a constant failure rate. 13 additional data sets are modeled, with 9 of the 14 data sets showing reliability growth approximately as n(t)/t =1/t or t-1and substantial final failure rates. The model fits most of the data sets, but 4of the 14 show no reliability growth. The reliability growth period typically includes six failures and extends one-quarter or half the total test time. As reliability growth testing continues, the cumulative failure rate should be tracked to estimate the reliability growth exponent and the final failure rate.
reliability growth modeling↗
Modeling Reliability Growth
Reliability growth has been modelled as an exponential decline in the cumulative failure rate that continues indefinitely as long as testing continues. Contrary to this, most reliability growth data show a brief high initial failure rate due to infant mortality followed by a long period of constant low failure rate. A two part failure rate model with an initial exponential decline followed by a constant failure rate usually fits the data and provides a more realistic description of reliability growth. The reliability growth process consists of testing, experiencing failures, finding the failure causes, and redesigning the system to remove them. The cost of reliability growth increases with the number of inherent failure modes and the time needed for them to occur and be removed. The failure modes with the lower failure rates will tend to occur later, as their Mean Time Before Failure (MTBF) is the inverse of the failure rate. Reliability growth testing has diminishing returns, since it takes longer to find and remove the less probable failures.This paper first discusses the reliability bathtub curve and then explains that reliability growth is produced by testing, identifying failure causes, and designing to remove them. A simple model of reliability growth is introduced, with a brief group of early failures followed by a constant failure rate. The cumulative failure rate n(t)/t can decline as rapidly as1/t or t-1butdeclines more slowly if additiona lfailures occur. The 56-failure Crow data seti s used to demonstrate the two-phase model of reliability growth followed by a constant failure rate. 13 additional data sets are modeled, with 9 of the 14 data sets showing reliability growth approximately as n(t)/t =1/t or t-1and substantial final failure rates. The model fits most of the data sets, but 4of the 14 show no reliability growth. The reliability growth period typically includes six failures and extends one-quarter or half the total test time. As reliability growth testing continues, the cumulative failure rate should be tracked to estimate the reliability growth exponent and the final failure rate.
reliability growth modeling↗
Assuring reliability program effectiveness.
An attempt is made to provide simple identification and description of techniques that have proved to be most useful either in developing a new product or in improving reliability of an established product. The first reliability task is obtaining and organizing parts failure rate data. Other tasks are parts screening, tabulation of general failure rates, preventive maintenance, prediction of new product reliability, and statistical demonstration of achieved reliability. Five principal tasks for improving reliability involve the physics of failure research, derating of internal stresses, control of external stresses, functional redundancy, and failure effects control. A final task is the training and motivation of reliability specialist engineers.
Ball, L. W.↗
Failure analysis of electronic parts: Laboratory methods
Failure analysis test methods are presented for use in analyzing candidate electronic parts and in improving future design reliability. Each test is classified as nondestructive, semidestructive, or destructive. The effects upon applicable part types (i.e. integrated circuit, transitor) are discussed. Methodology is given for performing the following: immersion tests, radio graphic tests, dewpoint tests, gas ambient analysis, cross sectioning, and ultraviolet examination.
Anstead, R. J.↗
In-Space Inspection Needs: Opportunities for advanced NDE tools such as x-ray CT for additively manufactured parts, in-situ resource utilization, geological applications, and more
It is now 50 years since the first human presence on the surface of the Moon and as we strive to return with women and men in the next few years, we embrace new technical challenges, goals, and innovative solutions to address 21st century objectives. These new ambitions carry fresh challenges and risks, with the field of NDE playing an increasingly more relevant role towards meeting these essential goals. In recent years, more advanced NDE tools have triggered a rapid expansion of applications for the space industry. In particular, x-ray Computed Tomography (CT) has proven to be a trusted and powerful asset for spaceflight hardware inspection, as well as applied geotechnical analysis for natural materials (e.g., rocks, soils) for NASA and across industry. However, such methods have yet to be extended to “deep space” applications such as those that are now part of the US National Space Policy Directive (SPD-1) and the accelerated push to return humans to the Moon (i.e., Artemis). For this reason, advancing these powerful Earth-based laboratory methods via new technologies, integrated computational solutions, and creative engineering approaches is directly aligned with national space policies, as well as with multiple NASA Strategic Plan priorities. The use of x-ray CT at scales as fine as a few microns or smaller can identify spacecraft part failure modes relevant to quality assurance for flight hardware and AM parts such as those recently developed for ISS. This technology could also identify valuable metallic phases within geological materials (i.e., rocks or drill cores), enabling resource-relevant triage of samples for In-Situ Resource Utilization (ISRU) and high science value sample return to Earth laboratories. There is also significant application for 3D imaging tools for medical use such as inspecting protective gear as well as bone density degradation studies which are critical in establishing a sustained presence in space. Timing for development of these tools for space use is advantageous as we prepare for new opportunities in the next few years and recognize recent commercial technology advancements which make it feasible. Moreover, as NASA strives to take full advantage of developments in AM technologies, including In-Space Manufacturing (ISM), it is widely recognized that NDE tools such as CT will play an essential role in acceptance of these parts for widespread use. New in-space 3D inspection tools with complimentary technology such as AI-based automated feature recognition (accelerated by machine learning), rapid compositional analysis, and advanced sample manipulation, would be a game-changing step toward a new class of crew-based laboratory sensors once human outposts on the Moon are established.
In-Space Non-Destructive Evaluation↗
Mass and Reliability Source (MaRS) Database
The Mass and Reliability Source (MaRS) Database consolidates components mass and reliability data for all Oribital Replacement Units (ORU) on the International Space Station (ISS) into a single database. It was created to help engineers develop a parametric model that relates hardware mass and reliability. MaRS supplies relevant failure data at the lowest possible component level while providing support for risk, reliability, and logistics analysis. Random-failure data is usually linked to the ORU assembly. MaRS uses this data to identify and display the lowest possible component failure level. As seen in Figure 1, the failure point is identified to the lowest level: Component 2.1. This is useful for efficient planning of spare supplies, supporting long duration crewed missions, allowing quicker trade studies, and streamlining diagnostic processes. MaRS is composed of information from various databases: MADS (operating hours), VMDB (indentured part lists), and ISS PART (failure data). This information is organized in Microsoft Excel and accessed through a program made in Microsoft Access (Figure 2). The focus of the Fall 2017 internship tour was to identify the components that were the root cause of failure from the given random-failure data, develop a taxonomy for the database, and attach material headings to the component list. Secondary objectives included verifying the integrity of the data in MaRS, eliminating any part discrepancies, and generating documentation for future reference. Due to the nature of the random-failure data, data mining had to be done manually without the assistance of an automated program to ensure positive identification.
Valdenegro, Wladimir↗
A Confidence-Based Approach to Including Survivors in a Probabilistic TID Failure Assessment
A probabilistic total ionizing dose (TID) failure assessment is extended to include survivor data, enabling the bounding of failure probability to a desired confidence level (CL) without failure data. The extension provides an avenue for analyzing microelectronics tested for TID without reaching a failure mode, a scenario often encountered by missions utilizing commercial-off-the-shelf (COTS) technologies. Using the type-I censored likelihood formulation and a realistic upper bound on expected device performance, the failure probability space is bounded by confidence contours within the context of a variable environment. The framework accommodates any type of distribution assumed for the part failure or the environment under consideration. Furthermore, the framework can be utilized pre-emptively to plan future device TID tests, minimizing costs while meeting survival requirements. Heritage data may also be used as survivors to further minimize testing costs when parts are from the same lot, but the amount of constraint derived from heritage is limited. Altogether, the framework enables a formal, mathematically rigorous analysis of radiation tolerant devices tested to a maximum dose, as well as flight heritage, in a hardness assurance methodology.
confidence↗
The calibration of photographic and spectroscopic films. Part 1: Film batch variations of reciprocity failure in IIaO film. Part 2: Thermal and aging effects in relationship to reciprocity failure. P art 3: Shifting of reciprocity failure points as a function of thermal and aging effects
Reciprocity failure was examined for IIaO spectroscopic film. Three separate experiments were performed in order to study film batch variations, thermal and aging effects in relationship to reciprocity failure, and shifting of reciprocity failure points as a function of thermal and aging effects. The failure was examined over ranges of time between 5 and 60 seconds. The variation to illuminance was obtained by using thirty neutral density filters. A standard sensitometer device imprinted the wedge pattern on the film as exposure time was subjected to variation. Results indicate that film batch differences, temperature, and aging play an important role in reciprocity failure of IIaO spectroscopic film. A shifting of the failure points was also observed in various batches of film.
Peters, Kevin A.↗
On scheduling tasks with a quick recovery from failure
Multiprocessors used in life-critical real-time systems must recover quickly from failure. Part of this recovery consists of switching to a new task schedule which ensures that hard deadlines for critical tasks continue to be met. A dynamic programming algorithm is presented that ensures that backup, or contingency, schedules can be efficiently embedded within the original, 'primary' schedule to ensure that hard deadlines continue to be met in the face of up to a given maximum number of processor failures. Several illustrative examples are included.
Krishna, C. M.↗
Reliability prediction - an engineering appraisal.
Reliability predictions showing need of bench- mark with respect to component part failure rates
COMPONENT RELIABILITY↗
Design, analysis, and tests of a structural prototype Viking aeroshell. I - Aeroshell design and analysis. II - Test procedure and test results.
Two near optimum full-scale Viking aeroshell prototypes (140 deg ring-stiffened conical shells), differing only in base ring size, were designed and tested under uniform pressure to buckling failure. Part I describes the computerized design procedure which iterates between a design program based on approximate equations to determine skin and ring gages and ring spacings, and a sophisticated system of shell of revolution programs for more accurate analysis as a basis for redesign. Part II discusses fabrication techniques, test procedures, and test results. Both buckling and prebuckling data are compared with the theoretical predictions of Part I. Appropriate buckling knockdown factors for this type of construction are identified. Measured strains in skin and rings agreed well with theoretical predictions and the buckling pressure was in close agreement with the design ultimate pressure.
Heard, W. L., Jr.↗